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Reliability-based design for soil tillage machines
Authors:A Abo Al-kheer  A El-Hami  AM Mouazen
Institution:a Rouen Mechanics Laboratory, National Institute of Applied Sciences, France
b Faculty of Mechanical Engineering, Aleppo University, Syria
c Natural Resources Department, Cranfield University, MK43 0AL, United Kingdom
Abstract:Using classical design methods for tillage machines does not completely guarantee a safety and satisfactory performance, due in part to the randomness of tillage forces. This randomness is derived from the variability in soil engineering properties and the variations in tool design parameters and operational conditions. In this paper, a reliability-based design approach was developed, for the first time, by integrating the randomness of tillage forces into the design analysis of tillage machines, aiming at achieving reliable machines. The proposed approach was based on the uncertainty analysis of basic random variables and the failure probability of tillage machines. The failure probability was estimated according to two performance criteria related to the structural design requirement and the quality of tillage operation. Two reliability methods, namely the Monte Carlo simulation technique and the first-order reliability methods were used for this purpose. This approach was implemented for the design of a chisel plough shank.The results showed that there were many values of the shank dimensions that guaranteed the required reliability level. However, in order to achieve the best design solution from an economic point of view, minimizing the volume of the shank structure was integrated into the reliability-based design approach. This led to the reduction of the initial volume of the shank structure by 6.86%. It was concluded that integrating the economical constraint into the reliability-based design approach can lead to optimal designs of tillage tools that ensures the required reliability level at low cost.
Keywords:Reliability-based design  Tillage machines  Tillage forces  Failure probability
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